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feature_selection
- 自己编的特征选择程序，分别包括用顺序前进法(SFS),顺序后退法(SBS),增l 减r 法(l–r)、SFFS法进行选择的程序-own addendum to the feature selection procedures, including the use of sequential forward (SFS). back order (SBS), by reducing r l (l-r), SFFS method to choose the procedure
jiansuo
- 这是我本科的毕业设计做的关于医学图像的基于形状的图像检索。预处理用小波去噪 ，特征选用不变矩。-This is my undergraduate graduation design done on the medical images based on the shape of the image retrieval. Pretreatment with wavelet denoising, feature selection invariant moment.
Class-separability
- 类可分离性的判别，特征选择与特征提取的任务是求出一组对分类最有效的特征因此需要有定量分析比较的方法，判断所得到的特征维数及所使用特征是否对分类最有利，这种用以定量检验分类性能的准则称为类可分离性判据。 类别可分离性判据，用来检验不同的特征组合对分类性能好坏的影响，并用来导出特征选择与特征提取的方法。 理想准则：某组特征使分类器错误概率最小-Class separability of discrimination, feature selection and feature extract
Relief
- 经典特征选择程序，在特征提取完成后进行特征选择可以达到提取有用成分的目的-Feature selection procedure, after completion of the feature extraction feature selection can achieve the purpose of extracting useful components
LDA
- 线性判别分析（LDA）用于特征选择，可以对数据集或者图像提取有用特征，用于分类或者聚类等机器学习应用中-Linear Discriminant Analysis (LDA) for feature selection, application in dataset or image feature extraction, for classification or clustering applications in machine learning
adxcvbv
- 基于最大熵的汉语人名识别方法研究 针对人名的特点，建立了特征模板，并在此基础上提取了特征集，利用特征选择算法提取了有效特征，并建立了一个基于最大熵的人名识别模型。 -Chinese name based on the maximum entropy method for identifying the characteristics of names, the establishment of a feature template, and on this basis set of fe
featureselection
- 特征选择方法,matlab实现增 l减 r法 顺序后退法 SFFS 特征选择 顺序前进法特征选择-feature selection
AdaptiveFeatureSelectionforHyperspectralDataAnalys
- 高光谱数据分析中的自适应特征提取算法adaptive feature selection-Hyperspectral data analysis adaptive feature extraction algorithm adaptive feature selection
wenj
- adaboost FEATURE SELECTION USING ADABOOST FOR FACE EXPRESSION RECOGNITION-FEATURE SELECTION USING ADABOOST FOR FACE EXPRESSION RECOGNITION
Derya_Ozkan
- Feature Selection for Face Recognition Using a Genetic Algorithm
Rapid_Object_Detection
- A very fast and robust object detection framework. A very simple set of Haar like box features A commensurating Image representation (that enables fast calculation of features, feature scaling and normalization) Efficient feature selectio
eigenvalue_computation.tar
- 快速PCA计算方法，有效实现降维等操作，和特征选择-Fast PCA method of calculation of effective dimension reduction and other operations, and feature selection
Text_Feature_Extraction
- 文本特征提取方法研究。文本的表示及其特征项的选取是文本挖掘、信息检索的一个基本问题，它把从文本中抽取出的特征词进行量化来表示文本信息。-Text Feature Extraction. And characteristics of the text of that item selection is text mining, information retrieval is a basic problem, which to extract from the text to quantify t
A-Survey-of-Feature-Selection
- 对特征选择方法的发展历史和现状进行了跨学科的广泛调研，在此基础上总结提出了通用的方法定义和算法流程框架-A unifring approach to the definition of the feature selection problem and corresponding algorithm design framework are proposed based on a complete survey of a wide range of interdisciplinary res
Feature-selection
- 模式识别领域中特征选择原理，代码及操作过程-In the field of pattern recognition feature selection principle, the code and the operation of the process
feature-selection
- 它指的是使用计算机提取图像信息，决定每个图像的点是否属于一个图像特征。特征提取的结果是把图像上的点分为不同的子集，这些子集往往属于孤立的点、连续的曲线或者连续的区域。 -It refers to the use of computer to extract image information, decide whether each image point belongs to an image feature. The results of feature extraction is t
Relief-feature-selection
- Relief 特征选择算法matlab实现-Relief feature selection
2-separability-based-feature-s
- 2快速separability-based特征选择方法highdimensional遥感图像分类模式识别_guo_pattrec 41(8)1670 - 1670 1670 -2 A fast separability-based feature selection method for highdimensional remotely-sensed image classification Pattern Recognition 41 (8) 1670-1679 2008
code-Feature-Selection-using-Matlab
- 主要完成图像特征出提取，包括5个特征选择算法：SFS，SBS，SFBS-Descr iption The DEMO includes 5 feature selection algorithms: Sequential Forward Selection (SFS) Sequential Floating Forward Selection (SFFS) Sequential Backward Selection (SBS) Sequential Floating Bac
band-selection
- 基于图像对比度和波段相关性的波段选择算法，适用于高光谱图像的特征选择-Bands selection algorithm based on image contrast and correlation of bands for hyperspectral image feature selection